Optical Frequency Domain Reflectometry (OFDR) is an effective technique for extracting external sensory information from the response of an optical fiber. See, e.g., U.S. Pat. Nos. 6,545,760; 6,566,648; 5,798,521; and 7,538,883. OFDR systems rely on scattering mechanisms, such as Rayleigh or Bragg scatter, to monitor phenomena that change the time-of-flight delay (“delay”) or spectral response of the optical fiber (see, e.g. U.S. Pat. No. 8,714,026). Many optical scattering mechanisms, including but not limited to Rayleigh and Bragg scatter, are sensitive to both temperature and strain. Through fiber and/or transducer design, these mechanisms can be made to sense other external parameters, such as shape, position, pressure, etc.
Existing Rayleigh or Bragg scattering-based sensors cannot distinguish the difference between temperature and strain. Both temperature and strain effects appear as a shift in the sensor's spectral response and as a stretching or compressing of its delay response. In practical applications, this cross-sensitivity between temperature and strain can generate errors in the sensor's measurement. In more complicated sensors, such as those designed to measure shape and position, this cross-sensitivity also contributes to error in the sensor's measured output.
In fiber optic-based shape sensing, a multi-channel distributed strain sensing system is used to detect the change in strain for each of several cores within a multi-core optical shape sensing fiber, as described in U.S. Pat. No. 8,773,650, which is incorporated herein by reference. Multiple distributed strain measurements are combined using a system of equations to produce a set of physical measurements including curvature, twist, and axial strain as described in U.S. Pat. No. 8,531,655, which is also incorporated herein by reference. These physical measurements can be used to determine the distributed shape and position of the optical fiber. Shape and position computations may be performed using a linear shape computation matrix that is preferably calculated using a calibration process. This calibration matrix is a property of a given sensor, and it may be stored and applied to one or more subsequent sets of distributed strain measurements at each of multiple points along the optical fiber.
Multi-core fiber has been shown to be a practical, physically-realizable solution for distributed sensing. However, the shape sensing systems described in the above patents do not distinguish between temperature changes along the length of the fiber and axial strain changes along the length of the fiber. Moreover, an error can manifest for certain shape sensing fibers dependent on a combination of axial strain and temperature change applied to the sensing fiber. Another challenge is that a fiber's response to various stimuli also exhibits a nonlinear response. Such stimuli include strain, temperature, and extrinsically-applied twist. A linear shape computation matrix, such as described above, may not be sufficient to produce high accuracy results in the presence of these stimuli.
One aspect of the technology concerns an optical fiber that includes one or more primary optical cores having a first set of properties and one or more secondary optical cores having a second set of properties. The primary set of properties includes a first temperature response, and the secondary set of properties includes a second temperature response sufficiently different from the first temperature response to allow a sensing apparatus when coupled to the optical fiber to distinguish between temperature and strain on the optical fiber.
In example applications, the optical fiber is configured as a temperature sensor that senses temperature independently from strain.
In example applications, the optical fiber is configured as a strain sensor that senses strain independently from temperature.
In example applications, the difference in optical properties among the sets of cores is achieved by varying the doping level in each set of cores during fiber manufacture.
In an example application, the primary set of cores includes four cores, the secondary set of cores includes one core, and the primary and second sets of cores are helically twisted. In another example application, the primary set of cores include four cores, the secondary set of cores includes three cores, and the primary and second sets of cores are helically twisted. In yet another application, the primary and second sets of cores are configured such that one core runs down the central axis of the fiber and the remaining cores are arranged in a regular pattern at constant radius and traverse a helical path along the fiber.
In example embodiments, a temperature response coefficient that scales applied temperature change to measured spectral shift is at least 2% larger or smaller in the secondary core(s) than in the primary core(s) so that temperature can be distinguished from strain.
Another aspect of the technology concerns a method for interrogating an optical fiber having one or more primary optical cores with a first temperature response and one or more secondary optical cores with a second temperature response. The method includes the steps of detecting interferometric measurement data associated with each of the one or more primary optical cores and each of the one or more secondary optical cores when the optical fiber is placed into a sensing position, determining one or more compensation parameters that compensate for measurement errors caused by temperature variations along the optical fiber based on a difference between the first temperature response of the primary cores and the second temperature response of the secondary cores, compensating the detected interferometric measurement data using the one or more compensation parameters, and generating measurement data based on the compensated interferometric measurement data.
In example embodiments, the generated measurement data may be strain data compensated for temperature variations along the optical fiber and/or temperature data compensated for strain variations along the optical fiber.
In one example application, the further includes displaying the generated measurement data on a display or storing the measurement data in memory.
In example embodiments, the interferometric measurement data is detected using Optical Frequency Domain Reflectometry (OFDR) and the generated measurement data includes a fully-distributed measurement of both temperature and strain along the optical fiber.
In example embodiments, the optical fiber is a shape sensing fiber and the method further comprises a calculation of shape and position which accounts for a linear response and a non-linear response of the optical fiber to external stimuli in the detected interferometric measurement data. In this case, the non-linear response includes second-order responses to temperature, strain, twist, and curvature in the detected interferometric measurement data. The compensating step includes introducing a temperature measurement term in a shape computation matrix to eliminate twist measurement error resulting from the difference between the first temperature response of the primary cores and the second temperature response of the secondary cores, and wherein the temperature measurement term is based on the second temperature response.
A shape computation may be performed using multiple shape computation matrices to represent a system of equations that describe the linear and nonlinear responses of the optical fiber to external stimuli in the detected interferometric measurement data. The shape computation matrices characterize the linear and non-linear responses of the optical fiber including inter-dependence of first-order and second-order strain, temperature, twist, and curvature.
In example embodiments, calibration interferometric measurement data may be detected including linear and non-linear responses of the optical fiber after individually isolating each of multiple stimulus parameters including temperature, strain, twist, and curvature. The shape computation matrices are then compensated based on the calibration interferometric measurement data. Alternatively, calibration interferometric measurement data produced in response to multiple linearly-independent sets of stimuli vectors may be detected, and the shape computation matrices are calibrated based on the calibration interferometric measurement data to account for a non-minimized response to the multiple linearly-independent sets of stimuli vectors. Still further, the calibrated shape computation matrices may be applied to the detected interferometric measurement data using a calculated or approximated inverse of the Jacobian matrix of the system of equations. The approximation to the inverse of the Jacobian matrix of the system of equations may be pre-computed.
Example embodiments minimize or reduce a twist measurement error resulting from differences in strain and/or temperature response by tailoring a doping level of one or more of the cores.